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Copyright © 2016 Ningyu Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In the latest years, the rapid progress of urban computing has engendered big issues, which creates both opportunities and challenges. The heterogeneous and big volume of data and the big difference between physical and virtual worlds have resulted in lots of problems in quickly solving practical problems in urban computing. In this paper, we propose a general application framework of ELM for urban computing. We present several real case studies of the framework like smog-related health hazard prediction and optimal retain store placement. Experiments involving urban data in China show the efficiency, accuracy, and flexibility of our proposed framework.

Details

Title
ELM Meets Urban Big Data Analysis: Case Studies
Author
Zhang, Ningyu; Chen, Huajun; Chen, Xi; Chen, Jiaoyan
Publication year
2016
Publication date
2016
Publisher
John Wiley & Sons, Inc.
ISSN
16875265
e-ISSN
16875273
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1818440647
Copyright
Copyright © 2016 Ningyu Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.